





import gc
import tempfile
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device


_snake_case    :       Union[str, Any]		       =    False



class 							_UpperCAmelCase       (       unittest.TestCase       ):

  """simple docstring"""


  pass





@nightly
@require_torch_gpu
class 							_UpperCAmelCase       (       unittest.TestCase       ):

  """simple docstring"""


  def 							lowercase						(							self					:						Optional[int]	)				->		Optional[int]:
     # clean up the VRAM after each test
     super().tearDown()
     gc.collect()
     torch.cuda.empty_cache()






  def 							lowercase						(							self					:						Optional[int]	)				->		List[str]:
     __lowerCAmelCase				      =      VersatileDiffusionTextToImagePipeline.from_pretrained('shi-labs/versatile-diffusion'	)
     # remove text_unet
     pipe.remove_unused_weights()
     pipe.to(lowerCAmelCase_	)
     pipe.set_progress_bar_config(disable=lowerCAmelCase_	)

     __lowerCAmelCase				      =      'A painting of a squirrel eating a burger '
     __lowerCAmelCase				      =      torch.manual_seed(0	)
     __lowerCAmelCase				      =      pipe(
         prompt=lowerCAmelCase_   ,    generator=lowerCAmelCase_   ,    guidance_scale=7.5   ,    num_inference_steps=2   ,    output_type='numpy'	).images

     with tempfile.TemporaryDirectory() as tmpdirname:
        pipe.save_pretrained(lowerCAmelCase_	)
        __lowerCAmelCase				      =      VersatileDiffusionTextToImagePipeline.from_pretrained(lowerCAmelCase_	)
     pipe.to(lowerCAmelCase_	)
     pipe.set_progress_bar_config(disable=lowerCAmelCase_	)

     __lowerCAmelCase				      =      generator.manual_seed(0	)
     __lowerCAmelCase				      =      pipe(
         prompt=lowerCAmelCase_   ,    generator=lowerCAmelCase_   ,    guidance_scale=7.5   ,    num_inference_steps=2   ,    output_type='numpy'	).images

     assert np.abs(image - new_image	).sum() < 1e-5, "Models don't have the same forward pass"






  def 							lowercase						(							self					:						Tuple	)				->		Optional[int]:
     __lowerCAmelCase				      =      VersatileDiffusionTextToImagePipeline.from_pretrained(
         'shi-labs/versatile-diffusion'   ,    torch_dtype=torch.floataa	)
     pipe.to(lowerCAmelCase_	)
     pipe.set_progress_bar_config(disable=lowerCAmelCase_	)

     __lowerCAmelCase				      =      'A painting of a squirrel eating a burger '
     __lowerCAmelCase				      =      torch.manual_seed(0	)
     __lowerCAmelCase				      =      pipe(
         prompt=lowerCAmelCase_   ,    generator=lowerCAmelCase_   ,    guidance_scale=7.5   ,    num_inference_steps=5_0   ,    output_type='numpy'	).images

     __lowerCAmelCase				      =      image[0, 2_5_3:2_5_6, 2_5_3:2_5_6, -1]

     assert image.shape == (1, 5_1_2, 5_1_2, 3)
     __lowerCAmelCase				      =      np.array([0.33_67, 0.31_69, 0.26_56, 0.38_70, 0.47_90, 0.37_96, 0.40_09, 0.48_78, 0.47_78]	)

     assert np.abs(image_slice.flatten() - expected_slice	).max() < 1e-2



"""simple docstring"""






class 			lowercase					:






			def __init__(self  :	Dict			)       ->	List[Any]:





				"""simple docstring"""


				lowerCAmelCase												=  {}






			def 					UpperCAmelCase							(self  :	Union[str, Any]			)       ->	None:





				"""simple docstring"""


				print(self.vertex			)
				for i in self.vertex:
					print(SCREAMING_SNAKE_CASE_      ,''' -> '''      ,''' -> '''.join([str(SCREAMING_SNAKE_CASE_			) for j in self.vertex[i]]			)			)






			def 					UpperCAmelCase							(self  :	Optional[Any]      ,SCREAMING_SNAKE_CASE_  :	int      ,SCREAMING_SNAKE_CASE_  :	int			)       ->	None:





				"""simple docstring"""


				if from_vertex in self.vertex:
					self.vertex[from_vertex].append(SCREAMING_SNAKE_CASE_			)
				else:
					# else make a new vertex
					lowerCAmelCase												=  [to_vertex]






			def 					UpperCAmelCase							(self  :	List[str]			)       ->	None:





				"""simple docstring"""


				lowerCAmelCase												=  [False] * len(self.vertex			)

				# call the recursive helper function
				for i in range(len(self.vertex			)			):
					if not visited[i]:
						self.dfs_recursive(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_			)






			def 					UpperCAmelCase							(self  :	Optional[Any]      ,SCREAMING_SNAKE_CASE_  :	int      ,SCREAMING_SNAKE_CASE_  :	list			)       ->	None:





				"""simple docstring"""


				lowerCAmelCase												=  True

				print(SCREAMING_SNAKE_CASE_      ,end=''' '''			)

				# Recur for all the vertices that are adjacent to this node
				for i in self.vertex:
					if not visited[i]:
						self.dfs_recursive(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_			)


if __name__ == "__main__":
					UpperCAmelCase        =				Graph()
					g.add_edge(0, 1)
					g.add_edge(0, 2)
					g.add_edge(1, 2)
					g.add_edge(2, 0)
					g.add_edge(2, 3)
					g.add_edge(3, 3)

					g.print_graph()
					print("""DFS:""")
					g.dfs()

					# OUTPUT:
					# 0  ->  1 -> 2
					# 1  ->  2
					# 2  ->  0 -> 3
					# 3  ->  3
					# DFS:
					#  0 1 2 3


